The present invention relates to image processing apparatus and more particularly, to an image processing apparatus which visually facilitates setting operation necessary for image processing by making use of the coordinate transformation.
A monitor apparatus has hitherto been used widely in which an input image representing an image of an area to be monitored that is picked up with an image pickup unit mounted with a solid imaging device such as a CCD (Charge Coupled Device) or CMOS (Complementary Metal-Oxide Semiconductor), for example, is processed by means of an image processing unit to automatically detect a given object transcribed in the input image. As an example of the method for automatic detection of an object (body) in an input image, a method called a difference method (background difference method) has been used.
In an object detection method based on the background difference method, the difference in brightness (or pixel value) between an input image obtained from the image pickup unit and a background image (reference image) picked up under disappearance of an object to be detected is calculated, the thus obtained difference image is binarized at predetermined thresholds to provide a digital image and then the supervision is waged on the presumption that the object to be detected will possibly exist in an area in which the size thereof reaches a predetermined size in the binarized image (change area).
The background difference method is diagrammatically illustrated in FIG. 7.
An input image 51 contains an image 52 of a human figure. On the other hand, a background image 53 is prepared in advance. A difference between input image 51 and background image 53 is calculated in respect of individual pixels by means of a difference calculator 54 to consequently obtain a difference image 55. In the difference image 55, the human figure image 52 transcribed in the input image 51 is detected as a pixel group 56 created by the difference.
Next, values of individual pixels of difference image 55 are compared with a threshold value (for example, 20 for one pixel supposed to be of 8 bits) by means of a binary digitization unit 57 so that pixels exceeding the threshold value may be converted to “255” and pixels less than the threshold may be converted to “0”. Through the process as above, a binarized image 58 can be obtained. In the binarized image, the area 56 producing the difference in the difference image 55 is detected as a binarized pixel group 59. It should be understood that the pixel group representing an ideal human figure is detected in FIG. 7 but sometimes, an object which is an originally single object will be detected in the form of a plurality of pixel groups or originally plural objects will be detected in the form of a single pixel group.
Further, by way of a grouping or labeling process in which lumps of binarized pixel 59 are subjected to grouping (by consulting the position and size of the previously detected lump) and the same number is assigned to the same object as the preceding one, the object detection can be accomplished. The result of detection can be obtained as an image in which the object is marked by a rectangular frame having predetermined width and height such as area 60 or by numerical values indicative of the position and size (height and width) of the object.
In addition to the background difference, various kinds of detection methods have been known including an inter-frame difference method and an optical flow method.
Incidentally, in an unattended monitor system, an object detected from a picked-up image through the aforementioned method is confirmed, with a view to reducing erroneous information, as to whether to be a true object to be detected by comparing information representing a reference (reference information) with information of the object extracted from the input image to make a decision (judgment), for example. The reference information (parameters) includes, for example, information concerning the position and size of the object to be detected.
More particularly, a parameter for deciding a target object as to which area in a picked-up input image the target object exists in is set in advance and it is then decided whether the position of the target object (for example, a ground position) is present inside the area. The parameter for settling the area is called an area parameter. In addition, in conformity with the size of an object to be detected (for example, a person), the range of size of the object to be detected is designated. This range is called a size parameter.
For example, in setting the area parameter, an input image is displayed on a display unit and apices of a polygon are set on the display screen by using an operation unit such as a mouse, thereby designating a desired area.
An example of an input image 71 is illustrated in FIG. 9.
For example, when an object approaching a building 72 in the input image 71 is to be detected, an area of a polygon 73 (dotted portion in the figure), for instance, is designated in the input image 71 as illustrated by using a predetermined designation unit.
Then, by deciding whether an object having a size meeting a size parameter is detected within the designated polygon through, for example, the difference method, a particular object approaching the building 72 (intruder or the like) can be detected.
Object detection techniques are disclosed in JP-A-2006-211696 corresponding to U.S. Pat. No. 6,812,835, JP-A-2005-57743 corresponding to U.S. Patent Application Publication No. 2005/0018879, JP-A-2001-273500 and JP-A-7-37063.